In three-dimensional (3D) image processing (e.g., 3D computer graphics, 3D modeling, 3D motion picture generation, etc.) information regarding object depth from a viewpoint is often used. For example, a depth map (e.g., an image or image channel) containing information relating to the distance of the surfaces of scene objects from a viewpoint may be used in providing depth information in association with a two-dimensional (2D) image.
Unfortunately, capturing or otherwise obtaining high resolution depth information is often difficult. For example, although cameras operable to capture high resolution 2D images (referred to herein as image cameras) are quite common (e.g., so common as to be included in many consumer devices, such as cellular phones, tablet devices, and notebook computers) and relatively inexpensive, the proliferation of cameras operable to capture depth information for a scene (referred to herein as depth cameras) are considerably less common and relatively expensive. Such depth cameras generally provide low resolution depth information, and thus may not map accurately to a corresponding high resolution image.
Although various techniques for providing upsampling or interpolation of low resolution depth information to higher resolution depth information have been tried, the techniques have not been wholly satisfactory. For example, the prior art interpolation techniques apply interpolative algorithms that examine depth samples which include unreliable samples, thereby tainting the interpolated results with unreliable sample inputs. The prior art interpolation techniques additionally cannot accurately identify depth discontinuities, and thus result in blurred and inaccurate object boundaries in the generated depth map. Moreover, the prior art interpolation techniques tend to require significant processing, such as due to performing bilateral filtering or interpolation for each pixel, implementing relatively large interpolation sample window sizes, etc. Accordingly, the resulting upsampled depth maps are often inaccurate at the cost of considerable processing resources.